Project Summary A major goal of DILIN since its inception has been to identify genetic biomarkers that predict predisposition to DILI and a poor prognosis. DILIN has identified both drug specific and general biomarkers for predisposition to DILI. The majority of these genetic biomarkers involve HLA alleles. In the last several years, Dr. Nicoletti has been working extensively on the predisposition to drug induced liver injury and recently joined the DILIN consortium. Dr. Nicoletti has been actively involved in the ongoing DILIN genetic projects that profiled DILI cases based on HLA alleles and common variants. She will continue to take an active role in carrying out the ongoing GWAS and PrediXscan analyses. Given her extensive experience on HLA allele prediction algorithms using both genotyped and sequencing data and extensive experience on the subsequent association analyses at the level of HLA alleles, haplotypes, and HLA supertypes, Dr. Nicoletti is also directing the design/analysis and interpretation of the results of the DILIN HLA allele sequencing project in collaboration with Dr. Li, Dr. Chalasani, Dr. Barnhart, Dr. Phillips and other DILIN researchers. Appropriate non-DILI control data will be critical to these studies. These efforts led to several DILIN publications in the past year, but additional work remains to be done. In the past year, Dr. Nicoletti expanded her efforts dramatically to provide non-DILI control data and investigate genetic links between predisposition to DILI and other liver diseases. Dr. Nicoletti is in the unique position of having immediate access to drug exposed and disease controls via the Mount Sinai BioME Biobank, one of the largest biobanks, which has paired genetic and clinical data for more than 50,000 individuals. This biobank is heavily weighted towards those with liver disease since the liver division was the first to open its clinic patients to enrollment in BioME. Finally, Dr. Nicoletti discovered evidence that DILI might share genetic risk factors with other autoimmune liver diseases like primary biliary cirrhosis. By combining DILIN genetic data with the BioMe dataset and other appropriate dbGAP datasets, she hopes to evaluate the genetic similarity between DILI and other liver disease in order to better understand the pathophysiology of DILI and the role of the genetic variants in the autoimmune traits. Additional time and effort is needed to bring these studies to fruition. DILIN is requesting another year of supplemental support for Dr. Nicoletti's efforts.